entry_point stringlengths 1 65 | original_triton_python_code stringlengths 208 619k | optimised_triton_code stringlengths 1.15k 275k | repo_name stringlengths 7 115 | module_name stringlengths 1 65 | synthetic bool 1
class | uuid int64 0 18.5k | licenses listlengths 1 6 | stars int64 0 19.8k | sha stringlengths 40 40 | repo_link stringlengths 72 180 |
|---|---|---|---|---|---|---|---|---|---|---|
ConvLayer | import torch
import torch.nn as nn
class ConvLayer(nn.Module):
def __init__(self, in_channels: 'int', out_channels: 'int', kernel_size:
'int', stride: 'int'):
super().__init__()
self._conv = nn.Conv2d(in_channels=in_channels, out_channels=
out_channels, kernel_size=kernel_size... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.... | Inkln/StyleTransferWithCatalyst | ConvLayer | false | 8,294 | [
"Apache-2.0"
] | 11 | c3181ecdfd32160907efc2d9d917a55925c25c11 | https://github.com/Inkln/StyleTransferWithCatalyst/tree/c3181ecdfd32160907efc2d9d917a55925c25c11 |
Net | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | arefmalek/Demographics_Disenfranchisement | Net | false | 6,300 | [
"MIT"
] | 1 | f4ae8c0965cf1b1cab9b245c3f5f54d3b5fe9aba | https://github.com/arefmalek/Demographics_Disenfranchisement/tree/f4ae8c0965cf1b1cab9b245c3f5f54d3b5fe9aba |
GaussianNoiseSampler | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch import device
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
@triton.jit
def triton_poi_... | tritas/mixdat | GaussianNoiseSampler | false | 13,043 | [
"BSD-3-Clause"
] | 0 | 38fb10df76df55cc1eddba5375c7699c23771fb3 | https://github.com/tritas/mixdat/tree/38fb10df76df55cc1eddba5375c7699c23771fb3 |
L2Norm | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | Bin-ze/Food_detection | L2Norm | false | 17,007 | [
"Apache-2.0"
] | 4 | 1c1a067f12644f2b0289e49aec4637d580722f70 | https://github.com/Bin-ze/Food_detection/tree/1c1a067f12644f2b0289e49aec4637d580722f70 |
CatFusion | import torch
from torch import nn
class CatFusion(nn.Module):
def __init__(self):
super(CatFusion, self).__init__()
def forward(self, seq_features, img_features, fuse_dim=1, **kwargs):
return torch.cat((seq_features, img_features), dim=fuse_dim)
def get_inputs():
return [torch.rand([4,... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | Asichurter/MalFusionFSL | CatFusion | false | 16,979 | [
"MIT"
] | 4 | 713bf64cc07a3489f42941fd2299837075575ac0 | https://github.com/Asichurter/MalFusionFSL/tree/713bf64cc07a3489f42941fd2299837075575ac0 |
CNN | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | EricZLou/Ax | CNN | false | 9,023 | [
"MIT"
] | 0 | 3f8fc6f4a055e93cb69fda3799be41ee9572ef02 | https://github.com/EricZLou/Ax/tree/3f8fc6f4a055e93cb69fda3799be41ee9572ef02 |
TorchModule | import torch
import torch.nn
class TorchLinearModule(torch.nn.Module):
def __init__(self, in_size, out_size):
super(TorchLinearModule, self).__init__()
self._linear = torch.nn.Linear(in_size, out_size)
def forward(self, x):
return self._linear(x)
class TorchModule(torch.nn.Module):... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn
ass... | alierenak/ivy | TorchModule | false | 1,413 | [
"Apache-2.0"
] | 0 | 6e91bae159101abbac904a0dd37d0f59daaa75e3 | https://github.com/alierenak/ivy/tree/6e91bae159101abbac904a0dd37d0f59daaa75e3 |
AverageAttention | import torch
import torch.nn as nn
import torch.cuda
import torch.distributed
class ActivationFunction(object):
relu = 'relu'
gelu = 'gelu'
class PositionwiseFeedForward(nn.Module):
""" A two-layer Feed-Forward-Network with residual layer norm.
Args:
d_model (int): the size of input for the... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.cuda
import torch.distributed
assert_size_str... | MaxatTezekbayev/OpenNMT-py-lexical | AverageAttention | false | 5,589 | [
"MIT"
] | 1 | 44182999b863fc4074d67e0281c5bdab19abddfe | https://github.com/MaxatTezekbayev/OpenNMT-py-lexical/tree/44182999b863fc4074d67e0281c5bdab19abddfe |
DiceLoss | import torch
import torch.nn as nn
class DiceLoss(nn.Module):
"""
This class implements the dice loss for multiple instances
"""
def __init__(self, smooth_factor: 'float'=1.0) ->None:
super(DiceLoss, self).__init__()
self.smooth_factor = smooth_factor
def __repr__(self):
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | ChristophReich1996/Cell-DETR | DiceLoss | false | 13,486 | [
"MIT"
] | 55 | 4d0c3a2d3ffd19184c8443e5b3a6dccc053c77ea | https://github.com/ChristophReich1996/Cell-DETR/tree/4d0c3a2d3ffd19184c8443e5b3a6dccc053c77ea |
Accuracy | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | ChristophReich1996/Cell-DETR | Accuracy | false | 13,479 | [
"MIT"
] | 55 | 4d0c3a2d3ffd19184c8443e5b3a6dccc053c77ea | https://github.com/ChristophReich1996/Cell-DETR/tree/4d0c3a2d3ffd19184c8443e5b3a6dccc053c77ea |
FM | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | Jie-Yuan/Deeps | FM | false | 17,486 | [
"MIT"
] | 4 | b4acbb8e16b8ff5d181e70c3b549df0d818d0d76 | https://github.com/Jie-Yuan/Deeps/tree/b4acbb8e16b8ff5d181e70c3b549df0d818d0d76 |
GEGLU | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | transat/latent-diffusion | GEGLU | false | 10,926 | [
"MIT"
] | 0 | 1ea0d5bb3fb0fe3f7e8c42cbae91423780977f83 | https://github.com/transat/latent-diffusion/tree/1ea0d5bb3fb0fe3f7e8c42cbae91423780977f83 |
CosineSimilarityLoss | import torch
import torch.nn as nn
class CosineSimilarityLoss(nn.Module):
def __init__(self, dim=1, eps=1e-08):
super(CosineSimilarityLoss, self).__init__()
self.cos = nn.CosineSimilarity(dim=dim, eps=eps)
self.eps = eps
def forward(self, inputs, target):
scores = self.cos(in... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | LTTM/LSR | CosineSimilarityLoss | false | 5,479 | [
"Apache-2.0"
] | 1 | ab204895a86160a5d278fe3cee14c11532251218 | https://github.com/LTTM/LSR/tree/ab204895a86160a5d278fe3cee14c11532251218 |
SplAtConv1d | from torch.nn import Module
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import Conv1d
from torch.nn import ReLU
from torch.nn.modules.utils import _single
class DropBlock1d(object):
def __init__(self, *args, **kwargs):
raise NotImplementedError
class rSoftMax(nn.Mod... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Neronjust2017/challenge2020_test4 | SplAtConv1d | false | 9,481 | [
"BSD-2-Clause"
] | 0 | 6494107a459b563aa51f8ea75c580c17557b13af | https://github.com/Neronjust2017/challenge2020_test4/tree/6494107a459b563aa51f8ea75c580c17557b13af |
AlbertAttentionWithoutSkipConnection | from _paritybench_helpers import _mock_config
import math
import torch
import torch.utils.checkpoint
from torch import nn
class AlbertAttentionWithoutSkipConnection(nn.Module):
def __init__(self, config):
super().__init__()
if (config.hidden_size % config.num_attention_heads != 0 and not
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | twistedcubic/attention-rank-collapse | AlbertAttentionWithoutSkipConnection | false | 16,646 | [
"Apache-2.0"
] | 118 | 38b5df6dc2add25f6d945e48a6baf96862368c20 | https://github.com/twistedcubic/attention-rank-collapse/tree/38b5df6dc2add25f6d945e48a6baf96862368c20 |
SentenceMatrixLayer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | ayyyq/T-LSTM | SentenceMatrixLayer | false | 6,310 | [
"MIT"
] | 1 | 36dbc88ac710d3925851cd87c2368ecfc7061b70 | https://github.com/ayyyq/T-LSTM/tree/36dbc88ac710d3925851cd87c2368ecfc7061b70 |
RankingLoss | import torch
import torch.nn as nn
class RankingLoss(nn.Module):
"""
ref: https://arxiv.org/abs/2002.10857
"""
def __init__(self, m: 'float', gamma: 'float') ->None:
super(RankingLoss, self).__init__()
self.m = m
self.gamma = gamma
self.soft_plus = nn.Softplus()
d... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | alipay/Parameter_Inference_Efficient_PIE | RankingLoss | false | 3,087 | [
"Apache-2.0"
] | 0 | 660add7705432a526aa3335fff3d8cf1c7d015a4 | https://github.com/alipay/Parameter_Inference_Efficient_PIE/tree/660add7705432a526aa3335fff3d8cf1c7d015a4 |
GPT2Postprocessing | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import n... | tunib-ai/large-scale-lm-tutorials | GPT2Postprocessing | false | 16,631 | [
"Apache-2.0"
] | 128 | ca29ff9f945a59abcc3e3f1000c4d83de97973d4 | https://github.com/tunib-ai/large-scale-lm-tutorials/tree/ca29ff9f945a59abcc3e3f1000c4d83de97973d4 |
SeriesDecomp | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.fft
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo... | jianzhnie/TsFormer | SeriesDecomp | false | 3,732 | [
"Apache-2.0"
] | 0 | 47e362f02445ba00d5ab8db206667767e72faca7 | https://github.com/jianzhnie/TsFormer/tree/47e362f02445ba00d5ab8db206667767e72faca7 |
ConvNorm | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size... | AeroXi/Tacotron2-Mandarin | ConvNorm | false | 13,246 | [
"MIT"
] | 67 | b7bc213d1c1a9c3e2f2e11f69f586c2582010668 | https://github.com/AeroXi/Tacotron2-Mandarin/tree/b7bc213d1c1a9c3e2f2e11f69f586c2582010668 |
exponential | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_... | Hyunmok-Park/modular-metalearning-master | exponential | false | 11,493 | [
"MIT"
] | 0 | a7be61d7c48a62ec8c333b1031521977baed792b | https://github.com/Hyunmok-Park/modular-metalearning-master/tree/a7be61d7c48a62ec8c333b1031521977baed792b |
Actor | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | XinJingHao/RL | Actor | false | 18,101 | [
"MIT"
] | 6 | eed54d6602b173e45ede722b0fcf82b5a203f14a | https://github.com/XinJingHao/RL/tree/eed54d6602b173e45ede722b0fcf82b5a203f14a |
ChannelMixer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn.fun... | GimmeSpoon/mlp-singer | ChannelMixer | false | 5,211 | [
"MIT"
] | 1 | 36d10a23c46fa7400994ccd063de79ff089efd5e | https://github.com/GimmeSpoon/mlp-singer/tree/36d10a23c46fa7400994ccd063de79ff089efd5e |
MaskUpdate | import torch
from torch import nn
from torch.nn.parameter import Parameter
class MaskUpdate(nn.Module):
def __init__(self, alpha):
super(MaskUpdate, self).__init__()
self.updateFunc = nn.ReLU(False)
self.alpha = Parameter(torch.tensor(alpha, dtype=torch.float32))
def forward(self, in... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch ... | DLwbm123/LBAM_inpainting | MaskUpdate | false | 17,192 | [
"MIT"
] | 7 | c809c3cedf09cda7c175e930c7834ac39d8f526f | https://github.com/DLwbm123/LBAM_inpainting/tree/c809c3cedf09cda7c175e930c7834ac39d8f526f |
InstanceSimilarity | import torch
import torch.nn.functional as F
import torch.nn as nn
class InstanceSimilarity(nn.Module):
"""
Instance Similarity based loss
"""
def __init__(self, mse=True):
super(InstanceSimilarity, self).__init__()
self.mse = mse
def _loss(self, fm_s, fm_t):
fm_s = fm_s.... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Tiamat-Tech/ZAQ-code | InstanceSimilarity | false | 14,497 | [
"MIT"
] | 55 | e7e9f55791e36c6784d58c356d3ced76a7583369 | https://github.com/Tiamat-Tech/ZAQ-code/tree/e7e9f55791e36c6784d58c356d3ced76a7583369 |
Attention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | wptoux/attention-ocr | Attention | false | 16,735 | [
"MIT"
] | 57 | ed08719db86a2aaf7e0cbae6169d9919835879d7 | https://github.com/wptoux/attention-ocr/tree/ed08719db86a2aaf7e0cbae6169d9919835879d7 |
CenterCosineSimilarity | import torch
import torch.nn as nn
class CenterCosineSimilarity(nn.Module):
def __init__(self, feat_dim, num_centers, eps=1e-08):
super(CenterCosineSimilarity, self).__init__()
self.centers = nn.Parameter(torch.randn(num_centers, feat_dim))
self.eps = eps
def forward(self, feat):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | GT-RIPL/DistillMatch-SSCL | CenterCosineSimilarity | false | 17,282 | [
"MIT"
] | 9 | e572671fd6994b3c43ad6e46e9efb3588804524c | https://github.com/GT-RIPL/DistillMatch-SSCL/tree/e572671fd6994b3c43ad6e46e9efb3588804524c |
group | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | JunhongH/CP-GAN | group | false | 17,523 | [
"Apache-2.0"
] | 9 | 5ac129da8cf6d010dc0da03bb4637d20c822d50b | https://github.com/JunhongH/CP-GAN/tree/5ac129da8cf6d010dc0da03bb4637d20c822d50b |
ContrastiveLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | Akimoto-Cris/Pytorch_AMOC | ContrastiveLoss | false | 18,404 | [
"Apache-2.0"
] | 2 | d2587ff3cfdd555c537c021dd616844da63210b9 | https://github.com/Akimoto-Cris/Pytorch_AMOC/tree/d2587ff3cfdd555c537c021dd616844da63210b9 |
Hflip | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | YanivHollander/kornia | Hflip | false | 14,630 | [
"ECL-2.0",
"Apache-2.0"
] | 418 | ccd258d0956da89b1feca96448eff8e4969d405a | https://github.com/YanivHollander/kornia/tree/ccd258d0956da89b1feca96448eff8e4969d405a |
ScaledDotProductAttention | import torch
import numpy as np
import torch.nn as nn
class ScaledDotProductAttention(nn.Module):
"""Scaled dot-product attention mechanism."""
def __init__(self, attention_dropout=0.0):
"""Init.
Args:
attention_dropout: A scalar, dropout rate.
"""
super(ScaledDotPr... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | yumoh/pinyin2hanzi | ScaledDotProductAttention | false | 13,154 | [
"MIT"
] | 0 | 1cbb650d3dd3ec0a0f51be5822556634860ad612 | https://github.com/yumoh/pinyin2hanzi/tree/1cbb650d3dd3ec0a0f51be5822556634860ad612 |
ModAssign | import torch
class ModAssign(torch.nn.Module):
def __init__(self):
super(ModAssign, self).__init__()
def forward(self, x, y):
x %= y
return x
def get_inputs():
return [torch.rand([4, 4, 4, 4]), torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
@triton.jit
d... | PogChamper/torch2trt | ModAssign | false | 14,192 | [
"MIT"
] | 3,363 | 43b12627ec0de4d212efb6d02b07570205085ccc | https://github.com/PogChamper/torch2trt/tree/43b12627ec0de4d212efb6d02b07570205085ccc |
StableBCELoss | import torch
class StableBCELoss(torch.nn.modules.Module):
def __init__(self):
super(StableBCELoss, self).__init__()
def forward(self, input, target):
neg_abs = -input.abs()
loss = input.clamp(min=0) - input * target + (1 + neg_abs.exp()).log()
return loss.mean()
def get_in... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
assert_size_stride = t... | GenoM87/hubmap | StableBCELoss | false | 2,273 | [
"MIT"
] | 0 | 4acd11c373c6bb136ea9c6627a174ff02afa5986 | https://github.com/GenoM87/hubmap/tree/4acd11c373c6bb136ea9c6627a174ff02afa5986 |
GCN | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | mengtinglll/deepke | GCN | false | 16,036 | [
"Apache-2.0"
] | 173 | da1649865c496317b45f0b26e9ea599c9f509ed0 | https://github.com/mengtinglll/deepke/tree/da1649865c496317b45f0b26e9ea599c9f509ed0 |
Decoder | import torch
import torch.nn as nn
class Decoder(nn.Module):
def __init__(self, z_dim):
super(Decoder, self).__init__()
self.deconv1 = nn.ConvTranspose2d(z_dim, 128, kernel_size=4, stride
=1, bias=False)
self.deconv2 = nn.ConvTranspose2d(128, 64, kernel_size=4, stride=2,
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | AbinavRavi/VAE-KL | Decoder | false | 31 | [
"Apache-2.0"
] | 0 | af7a44b7952c2e5e1be4f3ffa12a3d859f4f4bdc | https://github.com/AbinavRavi/VAE-KL/tree/af7a44b7952c2e5e1be4f3ffa12a3d859f4f4bdc |
CausalConv2d | import torch
import torch.nn as nn
class WNConv2d(nn.Module):
def __init__(self, in_channel, out_channel, kernel_size, stride=1,
padding=0, bias=True, activation=None):
super().__init__()
self.conv = nn.utils.weight_norm(nn.Conv2d(in_channel, out_channel,
kernel_size, stride=s... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | imatge-upc/pixelcoordEDL | CausalConv2d | false | 6,881 | [
"MIT"
] | 1 | 353632feed6ac8c93758c1a2a1b7a477e7ff053c | https://github.com/imatge-upc/pixelcoordEDL/tree/353632feed6ac8c93758c1a2a1b7a477e7ff053c |
LN_Actor | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | RohanPankaj/apex | LN_Actor | false | 999 | [
"MIT"
] | 0 | 74e96386bf9446d1179106d6d65ea0368c1b5b27 | https://github.com/RohanPankaj/apex/tree/74e96386bf9446d1179106d6d65ea0368c1b5b27 |
SimpleACosModule | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._... | andreas-hommel/glow | SimpleACosModule | false | 3,311 | [
"Apache-2.0"
] | 0 | 2bbbf8188a2a941e85677c83f2146bbd076a262e | https://github.com/andreas-hommel/glow/tree/2bbbf8188a2a941e85677c83f2146bbd076a262e |
FactoredAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | ZVK/jukebox | FactoredAttention | false | 18,200 | [
"MIT"
] | 5 | 23fd6753f2892214ad3d97f6f2b59f8cc8d0c57a | https://github.com/ZVK/jukebox/tree/23fd6753f2892214ad3d97f6f2b59f8cc8d0c57a |
MIRB1 | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
class ConvBlock(nn.Module):
def __init__(self, in_channels, out_channels, groups=3):
super(ConvBlock, self).__init__()
self.in_channels = in_channels
self.out_channels = out_channels
self.groups = gro... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | wwjfsfs/wwjyyds | MIRB1 | false | 13,210 | [
"MIT"
] | 0 | 80cd6267fde7cd98838078a0d5178a557ceb7414 | https://github.com/wwjfsfs/wwjyyds/tree/80cd6267fde7cd98838078a0d5178a557ceb7414 |
ScaledDotProductAttention | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Aleph0Inc/HDSA-Dialog | ScaledDotProductAttention | false | 13,254 | [
"MIT"
] | 146 | 88e2604adb5dc38ae32205410b15b2ac39116ecd | https://github.com/Aleph0Inc/HDSA-Dialog/tree/88e2604adb5dc38ae32205410b15b2ac39116ecd |
MAB | import math
import torch
import numpy as np
import torch.nn.functional as F
import torch.nn as nn
def qkv_attention(queries, keys, values, presence=None):
"""
Transformer-like self-attention.
Args:
queries: Tensor of shape [B, N, d_k].
keys: Tensor of shape [B, M, d_k].
values: : Tensor... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | KohavTal/SCAE_Project | MAB | false | 8,407 | [
"Apache-2.0"
] | 40 | bc6d1c3697fcb9327dd96e9657c3299b47cf355e | https://github.com/KohavTal/SCAE_Project/tree/bc6d1c3697fcb9327dd96e9657c3299b47cf355e |
adaILN | import torch
import torch.onnx
from torch import nn
import torch
from torch.nn.parameter import Parameter
class adaILN(nn.Module):
def __init__(self, num_features, eps=1e-05):
super(adaILN, self).__init__()
self.eps = eps
self.rho = Parameter(torch.Tensor(1, num_features, 1, 1))
s... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.onnx
from torch import nn
import torch
from torch.nn.parameter imp... | rtolps/Cats2dogs_ONNX | adaILN | false | 10,739 | [
"MIT"
] | 0 | 9c18a9ea9c6ae65feb5c2a1a4c814d31999b6ffc | https://github.com/rtolps/Cats2dogs_ONNX/tree/9c18a9ea9c6ae65feb5c2a1a4c814d31999b6ffc |
OffsetNet | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | scenarios/dev | OffsetNet | false | 4,458 | [
"Apache-2.0"
] | 0 | 9f91ebc142cea1c31231d233571ad59460ab6fba | https://github.com/scenarios/dev/tree/9f91ebc142cea1c31231d233571ad59460ab6fba |
MAXATTN | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Hritikbansal/RNNs_SVA_OOD | MAXATTN | false | 17,392 | [
"MIT"
] | 4 | a1c73955342d9d35c49da5fcb7b315e37b0f75d1 | https://github.com/Hritikbansal/RNNs_SVA_OOD/tree/a1c73955342d9d35c49da5fcb7b315e37b0f75d1 |
SCLN | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | ishine/Cross-Speaker-Emotion-Transfer | SCLN | false | 6,906 | [
"MIT"
] | 1 | 9d38e8058f5abc06167bac244d8ace083e2a6220 | https://github.com/ishine/Cross-Speaker-Emotion-Transfer/tree/9d38e8058f5abc06167bac244d8ace083e2a6220 |
MultiAttributeLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
assert_size_stride = t... | GregoryEHunter/generalization_to_OOD_category_viewpoint_combinations | MultiAttributeLoss | false | 17,347 | [
"MIT"
] | 10 | 52aacbb3420639cae64ce65085c17b245e5ef865 | https://github.com/GregoryEHunter/generalization_to_OOD_category_viewpoint_combinations/tree/52aacbb3420639cae64ce65085c17b245e5ef865 |
Mish | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch import nn
assert_size_stride = torch._C._dynamo.gua... | AnikinNN/AI-58 | Mish | false | 38 | [
"MIT"
] | 0 | ca3e3e7fc4551cf23d7f76a3d4edaf0c625883b9 | https://github.com/AnikinNN/AI-58/tree/ca3e3e7fc4551cf23d7f76a3d4edaf0c625883b9 |
EnsembleLayer | import torch
import torch as th
from torch import nn as nn
class EnsembleLayer(nn.Module):
def __init__(self, ensemble_size, input_dim, output_dim):
super().__init__()
self.W = nn.Parameter(th.empty((ensemble_size, input_dim,
output_dim)), requires_grad=True).float()
nn.init.x... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch as th
from torch import nn as nn
assert_size_stride = torch._C._dyn... | LucasAlegre/sac-plus | EnsembleLayer | false | 17,609 | [
"MIT"
] | 9 | 829c8652bc07a420e855ace696ae44de5feb5379 | https://github.com/LucasAlegre/sac-plus/tree/829c8652bc07a420e855ace696ae44de5feb5379 |
MLP | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import numpy as np
from torch... | manfreddiaz/rl-laplacian | MLP | false | 3,974 | [
"MIT"
] | 0 | 034803adb5c20c3bb7822b18d675b762fdcc53dc | https://github.com/manfreddiaz/rl-laplacian/tree/034803adb5c20c3bb7822b18d675b762fdcc53dc |
act_PR | import torch
import torch.nn as nn
import torch.utils.model_zoo
class act_PR(nn.Module):
def __init__(self, affine=True):
super(act_PR, self).__init__()
self.prelu = nn.PReLU(num_parameters=1)
self.relu = nn.ReLU(inplace=False)
def forward(self, x):
out = (self.relu(x) + self... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import torch.utils.model_zoo
assert_size_stride = torch._C._dynamo.... | Cheeun/FDSR | act_PR | false | 4,969 | [
"MIT"
] | 1 | 28b1c3c102334c5336038d0a0f6e1fceb393659a | https://github.com/Cheeun/FDSR/tree/28b1c3c102334c5336038d0a0f6e1fceb393659a |
AbsModel | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch.nn import Module
from torch import Tensor
from torch.nn import... | coreylowman/avalanche | AbsModel | false | 6,477 | [
"MIT"
] | 1 | 9c1e7765f1577c400ec0c57260221bcffd9566a2 | https://github.com/coreylowman/avalanche/tree/9c1e7765f1577c400ec0c57260221bcffd9566a2 |
MaxMarginRankingLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import numpy as np
from torch import nn
assert_size_stride = torch._C._dynamo.guards.asse... | amirziai/CLIP4Clip | MaxMarginRankingLoss | false | 14,829 | [
"MIT"
] | 294 | d1f31c881ed897a513c29e62512cd56c482420e6 | https://github.com/amirziai/CLIP4Clip/tree/d1f31c881ed897a513c29e62512cd56c482420e6 |
SAB | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Behrouz-Babaki/NCG4CVRP | SAB | false | 4,902 | [
"MIT"
] | 1 | 87d63366c0b461f44ce8e982159a1e207af77b44 | https://github.com/Behrouz-Babaki/NCG4CVRP/tree/87d63366c0b461f44ce8e982159a1e207af77b44 |
SelfAttention | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
class SelfAttention(nn.Module):
def __init__(self, config):
super().__init__()
self.query = nn.Linear(config.hidden_size, config.hidden_size)
self.key = nn.Linear(config.hidden_size, config.hidden_size)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Zaaachary/CSQA | SelfAttention | false | 1,905 | [
"BSD-3-Clause"
] | 0 | 6da6e076f67e9458deacb665d31463db14c7d860 | https://github.com/Zaaachary/CSQA/tree/6da6e076f67e9458deacb665d31463db14c7d860 |
SparsemaxBisect | from torch.autograd import Function
import torch
import torch.nn as nn
def sparsemax_bisect(X, dim=-1, n_iter=50, ensure_sum_one=True):
"""sparsemax: normalizing sparse transform (a la softmax), via bisection.
Solves the projection:
min_p ||x - p||_2 s.t. p >= 0, sum(p) == 1.
Parameters
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch.autograd import Function
import torch.nn as nn
assert_size_stride = torch._C._... | mtreviso/entmax | SparsemaxBisect | false | 10,645 | [
"MIT"
] | 0 | 5b029d07fe00d7aacc77c8e684a5796d29287575 | https://github.com/mtreviso/entmax/tree/5b029d07fe00d7aacc77c8e684a5796d29287575 |
FakeRKHSConvNet | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | jfrancis71/pytorch-lightning-bolts | FakeRKHSConvNet | false | 3,829 | [
"Apache-2.0"
] | 0 | 8a4cf8f61644c28d6df54ccffe3a52d6f5fce5a6 | https://github.com/jfrancis71/pytorch-lightning-bolts/tree/8a4cf8f61644c28d6df54ccffe3a52d6f5fce5a6 |
SimpleAndModule | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | YaronBenAtar/glow | SimpleAndModule | false | 14,656 | [
"Apache-2.0"
] | 2,838 | a13706a4239fa7eaf059c670dc573e3eb0768f86 | https://github.com/YaronBenAtar/glow/tree/a13706a4239fa7eaf059c670dc573e3eb0768f86 |
BboxHead | import torch
import torch.nn as nn
from itertools import product as product
class BboxHead(nn.Module):
def __init__(self, inchannels=512, num_anchors=3):
super(BboxHead, self).__init__()
self.conv1x1 = nn.Conv2d(inchannels, num_anchors * 4, kernel_size=(
1, 1), stride=1, padding=0)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from itertools import product as product
assert_size_strid... | FacePerceiver/facer | BboxHead | false | 8,131 | [
"MIT"
] | 12 | cbb01dc457f3713050e89af7b2c9c0d98663842c | https://github.com/FacePerceiver/facer/tree/cbb01dc457f3713050e89af7b2c9c0d98663842c |
AuxiliaryConvolutions | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
from ite... | mosevg/ssd | AuxiliaryConvolutions | false | 10,723 | [
"MIT"
] | 0 | 8fd9f6cc376c027427531bcf475188ae43c4b2d6 | https://github.com/mosevg/ssd/tree/8fd9f6cc376c027427531bcf475188ae43c4b2d6 |
AMSoftmaxLoss | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | AyushExel/s3prl | AMSoftmaxLoss | false | 1,991 | [
"MIT"
] | 0 | 6531904e9621a778978b9cfef3ba9f582e56639a | https://github.com/AyushExel/s3prl/tree/6531904e9621a778978b9cfef3ba9f582e56639a |
CNN | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.utils
class CNN(nn.Module):
def __init__(self, e_char, filters, padding=1, kernel_size=5):
super(CNN, self).__init__()
self.e_char = e_char
self.filters = filters
self.padding = padding
self... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | stxxllbu/CS224n-winter-together | CNN | false | 16,501 | [
"Apache-2.0"
] | 468 | eae158ed8e88dc7c8638e25bac4c4fc8eeddcc8c | https://github.com/stxxllbu/CS224n-winter-together/tree/eae158ed8e88dc7c8638e25bac4c4fc8eeddcc8c |
LocalConv2d | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | JSharpClone/M3D-RPN- | LocalConv2d | false | 11,522 | [
"Apache-2.0"
] | 0 | 5192b095e921b5c054a66fd0ce948e67aee957be | https://github.com/JSharpClone/M3D-RPN-/tree/5192b095e921b5c054a66fd0ce948e67aee957be |
LxmertSelfAttentionLayer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Clemens123/transformers | LxmertSelfAttentionLayer | false | 11,815 | [
"Apache-2.0"
] | 0 | 22abe7bbc587c16ec30f9d1aa549dcbeba6e9e26 | https://github.com/Clemens123/transformers/tree/22abe7bbc587c16ec30f9d1aa549dcbeba6e9e26 |
BehlerAngular | import torch
import torch.nn as nn
import torch.utils.data
class BehlerAngular(nn.Module):
"""
Compute Behler type angular contribution of the angle spanned by three atoms:
:math:`2^{(1-\\zeta)} (1 + \\lambda \\cos( {\\theta}_{ijk} ) )^\\zeta`
Sets of zetas with lambdas of -1 and +1 are generated au... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C.... | Avinashpathapati/gnn_molecule | BehlerAngular | false | 16,943 | [
"MIT"
] | 3 | 84b5e92902c638694b872c42d010676bcd3d7658 | https://github.com/Avinashpathapati/gnn_molecule/tree/84b5e92902c638694b872c42d010676bcd3d7658 |
GLU | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | SeungyounShin/c3-gan | GLU | false | 14,393 | [
"BSD-2-Clause"
] | 105 | 1fae645674c896b4bcb93e910034519f470a6a96 | https://github.com/SeungyounShin/c3-gan/tree/1fae645674c896b4bcb93e910034519f470a6a96 |
BP | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | arjunsesh/lrr-neurips | BP | false | 6,239 | [
"MIT"
] | 1 | d78106daec1e729b02a0452f74a37bf004ed243c | https://github.com/arjunsesh/lrr-neurips/tree/d78106daec1e729b02a0452f74a37bf004ed243c |
MetaPathEmbedding | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | Hui-Li/MCRec_PyTorch | MetaPathEmbedding | false | 17,410 | [
"MIT"
] | 9 | da4da77d2cade40c0a1961481c8e47ac396d12ee | https://github.com/Hui-Li/MCRec_PyTorch/tree/da4da77d2cade40c0a1961481c8e47ac396d12ee |
AddCoords | import torch
import torch.nn as nn
class AddCoords(nn.Module):
def __init__(self, with_r=False):
super().__init__()
self.with_r = with_r
def forward(self, input_tensor):
"""
Args:
input_tensor: shape(batch, channel, x_dim, y_dim)
"""
batch_size, _,... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | jiangxiluning/TCPN | AddCoords | false | 6,940 | [
"Apache-2.0"
] | 1 | 916bd8455be5c784068b7bb5bd6226da3f2d95c7 | https://github.com/jiangxiluning/TCPN/tree/916bd8455be5c784068b7bb5bd6226da3f2d95c7 |
ConvChain | import torch
import torch.utils.data
import torch.nn as nn
def _get_activation(activation):
valid = ['relu', 'leaky_relu', 'lrelu', 'tanh', 'sigmoid']
assert activation in valid, 'activation should be one of {}'.format(valid)
if activation == 'relu':
return nn.ReLU(inplace=True)
if activation ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.utils.data
impor... | sutkarsh/ttools | ConvChain | false | 10,930 | [
"MIT"
] | 0 | a2e5fbf308566c0c54ab9d6ad1d9f8bc63f8fe99 | https://github.com/sutkarsh/ttools/tree/a2e5fbf308566c0c54ab9d6ad1d9f8bc63f8fe99 |
SpatialAttention | import torch
from torch import nn
class SpatialAttention(nn.Module):
def __init__(self, kernel_size=7):
super().__init__()
self.conv = nn.Conv2d(2, 1, kernel_size=kernel_size, padding=
kernel_size // 2)
self.sigmoid = nn.Sigmoid()
def forward(self, x):
max_result,... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_s... | LeftAttention/Attention-Codebase | SpatialAttention | false | 17,588 | [
"Apache-2.0"
] | 6 | 348ec66233a7c0f95a3cb5f0f11641e2a7a9b9c3 | https://github.com/LeftAttention/Attention-Codebase/tree/348ec66233a7c0f95a3cb5f0f11641e2a7a9b9c3 |
ScaledLeakyReLUSin | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_... | Ugness/CIPS_SR | ScaledLeakyReLUSin | false | 14,533 | [
"MIT"
] | 172 | abce872f5bc1b84afb9634a7dd1991e8c74d7616 | https://github.com/Ugness/CIPS_SR/tree/abce872f5bc1b84afb9634a7dd1991e8c74d7616 |
ComponentConditionBlock | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data.distributed
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda... | Johnson-yue/lffont | ComponentConditionBlock | false | 13,903 | [
"MIT"
] | 98 | f31f5a1cd6a075449a0f18aaafd945d373121e15 | https://github.com/Johnson-yue/lffont/tree/f31f5a1cd6a075449a0f18aaafd945d373121e15 |
Upsample_ | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | Dauriel/weather4cast2021 | Upsample_ | false | 360 | [
"Apache-2.0"
] | 0 | 29e818c4bcd488ec84b51558bf5392e4a887db70 | https://github.com/Dauriel/weather4cast2021/tree/29e818c4bcd488ec84b51558bf5392e4a887db70 |
IOU | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | AlvinWen428/BASNet | IOU | false | 11,186 | [
"MIT"
] | 0 | 2af21e0333204b8adcb9565b33a0bf72f5471db5 | https://github.com/AlvinWen428/BASNet/tree/2af21e0333204b8adcb9565b33a0bf72f5471db5 |
SinReLU | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | awlange/pysurvival | SinReLU | false | 14,928 | [
"Apache-2.0"
] | 242 | 841b9bc6ce700ba8898d2a1488aa9cd25ee7a8e6 | https://github.com/awlange/pysurvival/tree/841b9bc6ce700ba8898d2a1488aa9cd25ee7a8e6 |
down_shifted_conv2d | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | ajayjain/lmconv | down_shifted_conv2d | false | 14,782 | [
"MIT"
] | 69 | e00576de5118702c90493e88c6e459b0e45d1290 | https://github.com/ajayjain/lmconv/tree/e00576de5118702c90493e88c6e459b0e45d1290 |
SimpleLinearModule | import torch
import torch.nn.functional as F
import torch.jit
import torch.onnx
import torch.nn
class SimpleLinearModule(torch.nn.Module):
def __init__(self):
super(SimpleLinearModule, self).__init__()
def forward(self, input, weight, bias=None):
return F.linear(input + input, weight, bias)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._C... | briancoutinho/glow | SimpleLinearModule | false | 12,580 | [
"Apache-2.0"
] | 0 | 4c919d60b3c33296c4109aec8020a1733c98f5b5 | https://github.com/briancoutinho/glow/tree/4c919d60b3c33296c4109aec8020a1733c98f5b5 |
Decoder | import torch
import torch.nn as nn
class Decoder(nn.Module):
def __init__(self, latent_dim=4, obs_dim=2, nhidden=20):
super(Decoder, self).__init__()
self.relu = nn.ReLU(inplace=True)
self.fc1 = nn.Linear(latent_dim, nhidden)
self.fc2 = nn.Linear(nhidden, obs_dim)
def forward... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | TylerChoi1224/torchdiffeq | Decoder | false | 1,165 | [
"MIT"
] | 0 | 72f74d9651a58ab11cdadd60682f1b61e625ef53 | https://github.com/TylerChoi1224/torchdiffeq/tree/72f74d9651a58ab11cdadd60682f1b61e625ef53 |
Generator | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | ConstantineLignos/ersatz | Generator | false | 7,906 | [
"Apache-2.0"
] | 16 | 7d1b8f2e0904503a24615777520837bc8633cd0c | https://github.com/ConstantineLignos/ersatz/tree/7d1b8f2e0904503a24615777520837bc8633cd0c |
distLinear | import torch
import torch.nn as nn
from torch.nn.utils.weight_norm import WeightNorm
class distLinear(nn.Module):
def __init__(self, indim, outdim):
super(distLinear, self).__init__()
self.L = nn.Linear(indim, outdim, bias=False)
self.class_wise_learnable_norm = True
if self.class... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | raphael-baena/clean-train | distLinear | false | 12,932 | [
"MIT"
] | 0 | f65fcecc11203b12f27d14964944db6941b513cc | https://github.com/raphael-baena/clean-train/tree/f65fcecc11203b12f27d14964944db6941b513cc |
Encoder | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | CBIIT/NCI-DOE-Collab-Pilot2-Autoencoder_MD_Simulation_Data | Encoder | false | 13,430 | [
"MIT"
] | 51 | 2b1213f944cf5f2c60799099a469989a1f0a6d3a | https://github.com/CBIIT/NCI-DOE-Collab-Pilot2-Autoencoder_MD_Simulation_Data/tree/2b1213f944cf5f2c60799099a469989a1f0a6d3a |
IOUloss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dynamo.guard... | hyperfraise/ByteTrack | IOUloss | false | 15,556 | [
"MIT"
] | 1,039 | d742a3321c14a7412f024f2218142c7441c1b699 | https://github.com/hyperfraise/ByteTrack/tree/d742a3321c14a7412f024f2218142c7441c1b699 |
Fusion | import torch
import torch.nn as nn
class Fusion(nn.Module):
""" Crazy multi-modal fusion: negative squared difference minus relu'd sum
"""
def __init__(self):
super().__init__()
def forward(self, x, y):
return -(x - y) ** 2 + torch.relu(x + y)
def get_inputs():
return [torch.ra... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | Ruiver/CTCNet | Fusion | false | 17,887 | [
"Apache-2.0"
] | 6 | 539e55ec9fed06028379d35dfd5cd4074755ffd8 | https://github.com/Ruiver/CTCNet/tree/539e55ec9fed06028379d35dfd5cd4074755ffd8 |
PixelUnshuffle | import torch
from torch import nn
import torch.utils.data
class PixelUnshuffle(nn.Module):
"""
Initialize: inplanes, planes, upscale_factor
OUTPUT: (planes // upscale_factor^2) * ht * wd
"""
def __init__(self, downscale_factor=2):
super(PixelUnshuffle, self).__init__()
self._r = d... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._... | HwangToeMat/tmp | PixelUnshuffle | false | 9,082 | [
"Apache-2.0"
] | 0 | a4f48443b16b5e07a9cf95f54651ade8c7669134 | https://github.com/HwangToeMat/tmp/tree/a4f48443b16b5e07a9cf95f54651ade8c7669134 |
EmbeddingLayer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | EpiSci/SoCRATES | EmbeddingLayer | false | 17,254 | [
"MIT"
] | 6 | 901a896c5a765e3cb56f290188cde71c8707192d | https://github.com/EpiSci/SoCRATES/tree/901a896c5a765e3cb56f290188cde71c8707192d |
SmoothL1Loss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import functools
impor... | ChHanXiao/mmdetection | SmoothL1Loss | false | 9,159 | [
"Apache-2.0"
] | 0 | 324aa5a042857a9b57abe37385e1210709a20d02 | https://github.com/ChHanXiao/mmdetection/tree/324aa5a042857a9b57abe37385e1210709a20d02 |
ac_net | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | bigtreeljc/force_learning | ac_net | false | 3,213 | [
"MIT"
] | 0 | 183a7c96c411e282966604e3cb375ba49e91a88c | https://github.com/bigtreeljc/force_learning/tree/183a7c96c411e282966604e3cb375ba49e91a88c |
BondEnergyModule | import torch
import torch.nn
import torch.nn as nn
from itertools import repeat
def gen(src, index, dim=-1, out=None, dim_size=None, fill_value=0):
dim = range(src.dim())[dim]
if index.dim() == 1:
index_size = list(repeat(1, src.dim()))
index_size[dim] = src.size(dim)
index = index.vie... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn
import torch.nn as nn
from itertools import repeat
assert_size_... | torchmd/mdgrad | BondEnergyModule | false | 16,626 | [
"MIT"
] | 54 | 77bd7685b74b41acf54a9483546e1e8cb545eb01 | https://github.com/torchmd/mdgrad/tree/77bd7685b74b41acf54a9483546e1e8cb545eb01 |
Head | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Rming/DocTr | Head | false | 14,327 | [
"MIT"
] | 111 | e61e3d34f65d1bd70997f2e2e583f640b8779a3c | https://github.com/Rming/DocTr/tree/e61e3d34f65d1bd70997f2e2e583f640b8779a3c |
AdaIN | import torch
import torch.nn as nn
import torch.utils.data
class AdaIN(nn.Module):
def __init__(self, style_dim, num_features):
super().__init__()
self.norm = nn.InstanceNorm2d(num_features, affine=False)
self.fc = nn.Linear(style_dim, num_features * 2)
def forward(self, x, s):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | Noodles-321/RegistrationEval | AdaIN | false | 8,649 | [
"MIT"
] | 38 | 3631d3d5bd65acf980fcfed803fa6125970f3e88 | https://github.com/Noodles-321/RegistrationEval/tree/3631d3d5bd65acf980fcfed803fa6125970f3e88 |
PartitionedReLU | import torch
import torch.nn as nn
class PartitionedReLU(nn.ReLU):
def forward(self, x):
if isinstance(x, tuple):
x_c, x_p = x
else:
x_c, x_p = torch.chunk(x, 2, dim=-1)
return super().forward(x_c), super().forward(x_p)
def get_inputs():
return [torch.rand([4... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | skulick/self-attentive-parser | PartitionedReLU | false | 4,354 | [
"MIT"
] | 0 | 04a91e80cc05bcfe8f48145517f58e85f0c8ade6 | https://github.com/skulick/self-attentive-parser/tree/04a91e80cc05bcfe8f48145517f58e85f0c8ade6 |
SpatialAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | alexchungio/Scene-Classification-Competition | SpatialAttention | false | 6,170 | [
"Apache-2.0"
] | 1 | d936667ceba1c0b8f90eb266019f43ff27767534 | https://github.com/alexchungio/Scene-Classification-Competition/tree/d936667ceba1c0b8f90eb266019f43ff27767534 |
LinearExcitability | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
from torch import nn
from torch.nn.parameter import Parameter
assert... | mhmorta/continual-learning-1 | LinearExcitability | false | 4,004 | [
"MIT"
] | 0 | 959d5238d4dd015245592993b5d044572ab58c90 | https://github.com/mhmorta/continual-learning-1/tree/959d5238d4dd015245592993b5d044572ab58c90 |
SA_Module | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | KonarkPaul/COVID_Adv_attack_vulnerability_study | SA_Module | false | 5,455 | [
"MIT"
] | 1 | f0d1256d0d57a933dd86ccd5fe12d83f9f79ca9c | https://github.com/KonarkPaul/COVID_Adv_attack_vulnerability_study/tree/f0d1256d0d57a933dd86ccd5fe12d83f9f79ca9c |
TimeEncode | import torch
import numpy as np
class TimeEncode(torch.nn.Module):
def __init__(self, dimension):
super(TimeEncode, self).__init__()
self.dimension = dimension
self.w = torch.nn.Linear(1, dimension)
self.w.weight = torch.nn.Parameter(torch.from_numpy(1 / 10 ** np.
lins... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import numpy ... | IDSC-io/vre-tgn | TimeEncode | false | 9,143 | [
"Apache-2.0"
] | 0 | 46e8327e3befe67003874fa70b384a511523f8f7 | https://github.com/IDSC-io/vre-tgn/tree/46e8327e3befe67003874fa70b384a511523f8f7 |
MoEHead | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | cclauss/nonauto-nmt | MoEHead | false | 15,014 | [
"BSD-3-Clause"
] | 262 | efcbe4f2329b140ac3ce06abb6409457cebc8e49 | https://github.com/cclauss/nonauto-nmt/tree/efcbe4f2329b140ac3ce06abb6409457cebc8e49 |
AttentionScore | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | BruceWen120/neurips-reproducibility-challenge-2019 | AttentionScore | false | 8,945 | [
"Apache-2.0"
] | 0 | b0635aefe83e3f895ce0991913824e861bb7d02d | https://github.com/BruceWen120/neurips-reproducibility-challenge-2019/tree/b0635aefe83e3f895ce0991913824e861bb7d02d |
ConvSigmoidInplace | import torch
from torch import nn
import torch.cuda
import torch.backends.cudnn
import torch.backends.mkl
import torch.backends.cuda
import torch.backends.quantized
class ConvSigmoidInplace(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size, image_size):
super(ConvSigmoidInplace, self)... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
import torch.cuda
import torch.backends.cudnn
import torch.... | Observer007/intel-extension-for-pytorch | ConvSigmoidInplace | false | 5,667 | [
"Apache-2.0"
] | 1 | f8ab25c305c89d5aaf06190a4fec0727aeb4dcd7 | https://github.com/Observer007/intel-extension-for-pytorch/tree/f8ab25c305c89d5aaf06190a4fec0727aeb4dcd7 |
idct_8x8 | import itertools
import torch
import numpy as np
import torch.nn as nn
class idct_8x8(nn.Module):
""" Inverse discrete Cosine Transformation
Input:
dcp(tensor): batch x height x width
Output:
image(tensor): batch x height x width
"""
def __init__(self):
super(idct_8x8, sel... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import itertools
import numpy as np
import torch.nn as nn
assert_size_stride = t... | foxtrotmike/DiffJPEG | idct_8x8 | false | 12,397 | [
"MIT"
] | 0 | 7dbc44b1e921f20a213a7206a8578d6a1c8131b4 | https://github.com/foxtrotmike/DiffJPEG/tree/7dbc44b1e921f20a213a7206a8578d6a1c8131b4 |
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